{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "2fd1dfcf",
   "metadata": {},
   "outputs": [],
   "source": [
    "import xlwt\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import datetime\n",
    "import time\n",
    "from sqlalchemy import create_engine\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "ebde5604",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>日期</th>\n",
       "      <th>汇买价(元）</th>\n",
       "      <th>钞买价（元）</th>\n",
       "      <th>汇卖价（元）</th>\n",
       "      <th>钞卖价（元）</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2021/11/11</td>\n",
       "      <td>637.79</td>\n",
       "      <td>632.68</td>\n",
       "      <td>640.67</td>\n",
       "      <td>640.67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2021/11/10</td>\n",
       "      <td>637.57</td>\n",
       "      <td>632.46</td>\n",
       "      <td>640.45</td>\n",
       "      <td>640.45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2021/11/09</td>\n",
       "      <td>637.57</td>\n",
       "      <td>632.46</td>\n",
       "      <td>640.45</td>\n",
       "      <td>640.45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2021/11/08</td>\n",
       "      <td>637.92</td>\n",
       "      <td>632.81</td>\n",
       "      <td>640.80</td>\n",
       "      <td>640.80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2021/11/07</td>\n",
       "      <td>638.06</td>\n",
       "      <td>632.94</td>\n",
       "      <td>642.22</td>\n",
       "      <td>642.22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3895</th>\n",
       "      <td>2011/03/04</td>\n",
       "      <td>654.74</td>\n",
       "      <td>649.49</td>\n",
       "      <td>658.68</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3896</th>\n",
       "      <td>2011/03/03</td>\n",
       "      <td>655.49</td>\n",
       "      <td>650.23</td>\n",
       "      <td>658.11</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3897</th>\n",
       "      <td>2011/03/02</td>\n",
       "      <td>655.91</td>\n",
       "      <td>650.65</td>\n",
       "      <td>658.53</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3898</th>\n",
       "      <td>2011/03/01</td>\n",
       "      <td>655.69</td>\n",
       "      <td>650.43</td>\n",
       "      <td>658.31</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3899</th>\n",
       "      <td>2011/02/28</td>\n",
       "      <td>655.82</td>\n",
       "      <td>650.56</td>\n",
       "      <td>658.44</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3900 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              日期  汇买价(元）  钞买价（元）  汇卖价（元）  钞卖价（元）\n",
       "0     2021/11/11  637.79  632.68  640.67  640.67\n",
       "1     2021/11/10  637.57  632.46  640.45  640.45\n",
       "2     2021/11/09  637.57  632.46  640.45  640.45\n",
       "3     2021/11/08  637.92  632.81  640.80  640.80\n",
       "4     2021/11/07  638.06  632.94  642.22  642.22\n",
       "...          ...     ...     ...     ...     ...\n",
       "3895  2011/03/04  654.74  649.49  658.68     NaN\n",
       "3896  2011/03/03  655.49  650.23  658.11     NaN\n",
       "3897  2011/03/02  655.91  650.65  658.53     NaN\n",
       "3898  2011/03/01  655.69  650.43  658.31     NaN\n",
       "3899  2011/02/28  655.82  650.56  658.44     NaN\n",
       "\n",
       "[3900 rows x 5 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_excel(r'C:/Users/Mr.Xiao/Desktop/人民币美元汇率2011-2021.xlsx',sheet_name=0,)\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "8baeaf8a",
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, '汇买价波动情况')"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = df.iloc[:,1]\n",
    "y = df.index\n",
    "plt.plot(y,x,color='black')\n",
    "plt.title('汇买价波动情况',family='Microsoft YaHei')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "7ac9c9f2",
   "metadata": {},
   "outputs": [
    {
     "ename": "SyntaxError",
     "evalue": "invalid syntax (Temp/ipykernel_20332/1330855913.py, line 1)",
     "output_type": "error",
     "traceback": [
      "\u001b[1;36m  File \u001b[1;32m\"C:\\Users\\MR707B~1.XIA\\AppData\\Local\\Temp/ipykernel_20332/1330855913.py\"\u001b[1;36m, line \u001b[1;32m1\u001b[0m\n\u001b[1;33m    price_gap = [df.iloc[:,3]-df.iloc[:,1] as gap,df.iloc[:,0]]\u001b[0m\n\u001b[1;37m                                            ^\u001b[0m\n\u001b[1;31mSyntaxError\u001b[0m\u001b[1;31m:\u001b[0m invalid syntax\n"
     ]
    }
   ],
   "source": [
    "price_gap = [df.iloc[:,3]-df.iloc[:,1],df.iloc[:,0]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "82bb19de",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed 0</th>\n",
       "      <th>日期</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2.88</td>\n",
       "      <td>2021/11/11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2.88</td>\n",
       "      <td>2021/11/10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2.88</td>\n",
       "      <td>2021/11/09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2.88</td>\n",
       "      <td>2021/11/08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4.16</td>\n",
       "      <td>2021/11/07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3895</th>\n",
       "      <td>3.94</td>\n",
       "      <td>2011/03/04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3896</th>\n",
       "      <td>2.62</td>\n",
       "      <td>2011/03/03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3897</th>\n",
       "      <td>2.62</td>\n",
       "      <td>2011/03/02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3898</th>\n",
       "      <td>2.62</td>\n",
       "      <td>2011/03/01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3899</th>\n",
       "      <td>2.62</td>\n",
       "      <td>2011/02/28</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3900 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Unnamed 0          日期\n",
       "0         2.88  2021/11/11\n",
       "1         2.88  2021/11/10\n",
       "2         2.88  2021/11/09\n",
       "3         2.88  2021/11/08\n",
       "4         4.16  2021/11/07\n",
       "...        ...         ...\n",
       "3895      3.94  2011/03/04\n",
       "3896      2.62  2011/03/03\n",
       "3897      2.62  2011/03/02\n",
       "3898      2.62  2011/03/01\n",
       "3899      2.62  2011/02/28\n",
       "\n",
       "[3900 rows x 2 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "price_gap2 = pd.DataFrame(price_gap).T\n",
    "price_gap2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "f92dc9c7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, '汇买卖交易差价')"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 648x648 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(9,9))\n",
    "M= price_gap2.iloc[:,0]\n",
    "m= price_gap2.index\n",
    "plt.plot(m,M,color='green')\n",
    "plt.title('汇买卖交易差价',family='Microsoft Yahei')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "ab6b5b62",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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kNcJAl6RGGOiS1AgDXZIaYaBLUiMMdElqhIEuSY34f9SfiEzrAMn3AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "_=plt.hist(M,bins=100,density=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "689cc0ce",
   "metadata": {},
   "outputs": [],
   "source": [
    "change_rate = [df.iloc[:,2]-df.iloc[:,2].shift(periods=-1),df.iloc[:,0]] #两日差价"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "ce663def",
   "metadata": {},
   "outputs": [],
   "source": [
    "change_rate2 =pd.DataFrame(change_rate).T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "id": "e940e78c",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\users\\mr.xiao\\appdata\\local\\programs\\python\\python37\\lib\\site-packages\\numpy\\lib\\histograms.py:837: RuntimeWarning: invalid value encountered in greater_equal\n",
      "  keep = (tmp_a >= first_edge)\n",
      "c:\\users\\mr.xiao\\appdata\\local\\programs\\python\\python37\\lib\\site-packages\\numpy\\lib\\histograms.py:838: RuntimeWarning: invalid value encountered in less_equal\n",
      "  keep &= (tmp_a <= last_edge)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = change_rate2.iloc[:,0]\n",
    "y = change_rate2.index\n",
    "_=plt.hist(x,bins=50)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "abdfcf76",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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     ]
    }
   ],
   "source": [
    "month = []\n",
    "for i in change_rate2.iloc[:,1]:\n",
    "    print(i[5:7])\n",
    "    month.append(i[5:7])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "id": "810f06f6",
   "metadata": {},
   "outputs": [],
   "source": [
    "change_rate2['month']=month"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "id": "7b692cb6",
   "metadata": {},
   "outputs": [
    {
     "data": {
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      "text/plain": [
       "       钞买价（元）   日期\n",
       "month             \n",
       "03        102  102\n",
       "05        102  102\n",
       "07         99   99\n",
       "08         93   93\n",
       "04         88   88\n",
       "06         88   88\n",
       "11         88   88\n",
       "09         85   85\n",
       "12         84   84\n",
       "01         80   80\n",
       "02         79   79\n",
       "10         77   77"
      ]
     },
     "execution_count": 111,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "index = change_rate2.iloc[:,0]>=0.25\n",
    "change_rate2[index].groupby(by='month').count().sort_values(by='日期',ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "id": "4f5fe6d8",
   "metadata": {},
   "outputs": [
    {
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      "text/plain": [
       "       钞买价（元）   日期\n",
       "month             \n",
       "08        115  115\n",
       "09        104  104\n",
       "05        101  101\n",
       "03         99   99\n",
       "07         97   97\n",
       "04         95   95\n",
       "01         94   94\n",
       "10         89   89\n",
       "12         88   88\n",
       "06         79   79\n",
       "11         79   79\n",
       "02         66   66"
      ]
     },
     "execution_count": 113,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "index = change_rate2.iloc[:,0]<=-0.25\n",
    "change_rate2[index].groupby(by='month').count().sort_values(by='日期',ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "28685876",
   "metadata": {},
   "outputs": [],
   "source": [
    "l = [df.iloc[:,3],df.iloc[:,0]]\n",
    "df2= pd.DataFrame(l).T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "415ca2c2",
   "metadata": {},
   "outputs": [],
   "source": [
    "df2['month']=month"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "5bb6c99e",
   "metadata": {},
   "outputs": [],
   "source": [
    "year =[]\n",
    "for i in df2.iloc[:,1]:\n",
    "#     print(i[0:4])\n",
    "    year.append(i[0:4])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "e5a5b0f4",
   "metadata": {},
   "outputs": [],
   "source": [
    "df2['year']=year"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "2a22dfdd",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\users\\mr.xiao\\appdata\\local\\programs\\python\\python37\\lib\\site-packages\\pandas\\core\\apply.py:507: FutureWarning: Dropping invalid columns in DataFrameGroupBy.mean is deprecated. In a future version, a TypeError will be raised. Before calling .mean, select only columns which should be valid for the function.\n",
      "  return self._try_aggregate_string_function(obj, f, *self.args, **self.kwargs)\n"
     ]
    }
   ],
   "source": [
    "df4 =df2.pivot_table(index=['year','month'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "8ab7e56d",
   "metadata": {},
   "outputs": [],
   "source": [
    "K= np.linspace(1,130,130)\n",
    "k=[]\n",
    "for i in df2.pivot_table(index=['year','month']).values:\n",
    "    k.append(i)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 147,
   "id": "bd2ca6cf",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(K,k)\n",
    "_=plt.title('汇买价月均折线图',family='Microsoft Yahei',fontsize=12)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "920472cd",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\users\\mr.xiao\\appdata\\local\\programs\\python\\python37\\lib\\site-packages\\IPython\\core\\interactiveshell.py:3444: FutureWarning: Dropping invalid columns in DataFrameGroupBy.mean is deprecated. In a future version, a TypeError will be raised. Before calling .mean, select only columns which should be valid for the function.\n",
      "  exec(code_obj, self.user_global_ns, self.user_ns)\n"
     ]
    }
   ],
   "source": [
    "df3 = df2.groupby(by=['month','year']).mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "aa556680",
   "metadata": {},
   "outputs": [],
   "source": [
    "df4['price_shift']=df4.iloc[:,0].shift(periods=12)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "06e53034",
   "metadata": {},
   "outputs": [],
   "source": [
    "df4['year_gap']=df4['price_shift']-df4.iloc[:,0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 183,
   "id": "7b3e229b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, '同比价格差')"
      ]
     },
     "execution_count": 183,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "j=df4['year_gap']\n",
    "J=np.linspace(1,130,130)\n",
    "plt.plot(J,j)\n",
    "plt.title('同比价格差',family='Microsoft Yahei',fontsize=12)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "7df69fd7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>汇卖价（元）</th>\n",
       "      <th>price_shift</th>\n",
       "      <th>year_gap</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>year</th>\n",
       "      <th>month</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">2011</th>\n",
       "      <th>02</th>\n",
       "      <td>658.440000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>03</th>\n",
       "      <td>658.028065</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>04</th>\n",
       "      <td>654.468276</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>05</th>\n",
       "      <td>650.790937</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>06</th>\n",
       "      <td>648.930000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">2021</th>\n",
       "      <th>07</th>\n",
       "      <td>649.183667</td>\n",
       "      <td>703.148710</td>\n",
       "      <td>53.965043</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>08</th>\n",
       "      <td>649.502187</td>\n",
       "      <td>694.986129</td>\n",
       "      <td>45.483942</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>09</th>\n",
       "      <td>647.368000</td>\n",
       "      <td>683.309667</td>\n",
       "      <td>35.941667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>644.070000</td>\n",
       "      <td>673.717333</td>\n",
       "      <td>29.647333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>641.215455</td>\n",
       "      <td>662.461290</td>\n",
       "      <td>21.245836</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>130 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                汇卖价（元）  price_shift   year_gap\n",
       "year month                                    \n",
       "2011 02     658.440000          NaN        NaN\n",
       "     03     658.028065          NaN        NaN\n",
       "     04     654.468276          NaN        NaN\n",
       "     05     650.790937          NaN        NaN\n",
       "     06     648.930000          NaN        NaN\n",
       "...                ...          ...        ...\n",
       "2021 07     649.183667   703.148710  53.965043\n",
       "     08     649.502187   694.986129  45.483942\n",
       "     09     647.368000   683.309667  35.941667\n",
       "     10     644.070000   673.717333  29.647333\n",
       "     11     641.215455   662.461290  21.245836\n",
       "\n",
       "[130 rows x 3 columns]"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "7b41ad9b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='month', ylabel='year_gap'>"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.lineplot(x='month',y='year_gap',hue='year',data=df4)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f351c158",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.4"
  },
  "toc": {
   "base_numbering": 1,
   "nav_menu": {},
   "number_sections": true,
   "sideBar": true,
   "skip_h1_title": false,
   "title_cell": "Table of Contents",
   "title_sidebar": "Contents",
   "toc_cell": false,
   "toc_position": {},
   "toc_section_display": true,
   "toc_window_display": false
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
